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Existing datasets for automated fact-checking have substantial limitations, such as relying on artificial claims, lacking annotations for evidence and intermediate reasoning, or including evidence published after the claim.
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H. W. Kuhn · 1955
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ROUGE: A package for automatic evaluation of summaries
Chin-Yew Lin · 2004
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METEOR: An automatic metric for MT evaluation with improved correlation with human judgments
Satanjeev Banerjee and Alon Lavie · 2005
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Justus J Randolph · 2005
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Stephen Robertson and Hugo Zaragoza · 2009
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Matthijs J Warrens · 2010
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Computational journalism: A call to arms to database researchers
Sarah Cohen, Chengkai Li, Jun Yang, and Cong Yu · 2011
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The Epistemology of Fact Checking
Joseph E. Uscinski and Ryden W. Butler · 2013
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Revisiting the Epistemology of Fact-Checking
Michelle A. Amazeen · 2014
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Fact checking: Task definition and dataset construction
Andreas Vlachos and Sebastian Riedel · 2014
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Detecting check-worthy factual claims in presidential debates
Naeemul Hassan, Chengkai Li, and Mark Tremayne · 2015
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Adam: A method for stochastic optimization
Diederik P. Kingma and Jimmy Ba · 2015
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The Chicago Guide to Fact-checking
Brooke Borel · 2016
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Taking MT Evaluation Metrics to Extremes: Beyond Correlation with Human Judgments
Marina Fomicheva and Lucia Specia · 2017
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Fully automated fact checking using external sources
Georgi Karadzhov, Preslav Nakov, Lluís Màrquez, Alberto Barrón-Cedeño, and Ivan Koychev · 2017
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Where is your evidence: Improving fact-checking by justification modeling
Tariq Alhindi, Savvas Petridis, and Smaranda Muresan · 2018
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Data statements for natural language processing: Toward mitigating system bias and enabling better science
Emily M. Bender and Batya Friedman · 2018
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Algorithms of oppression
Safiya Umoja Noble · 2018
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FEVER: a large-scale dataset for fact extraction and VERification
James Thorne, Andreas Vlachos, Christos Christodoulopoulos, and Arpit Mittal · 2018
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MultiFC: A real-world multi-domain dataset for evidence-based fact checking of claims
Isabelle Augenstein, Christina Lioma, Dongsheng Wang, Lucas Chaves Lima, Casper Hansen, Christian Hansen, and Jakob Grue Simonsen · 2019
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The When, Why, How and So-What of Verifications
Aviv Barnoy and Zvi Reich · 2019
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BERT: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova · 2019
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A richly annotated corpus for different tasks in automated fact-checking
Andreas Hanselowski, Christian Stab, Claudia Schulz, Zile Li, and Iryna Gurevych · 2019
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Automated fact checking in the news room
Automated fact-checking for assisting human fact-checkers
Preslav Nakov, David Corney, Maram Hasanain, Firoj Alam, Tamer Elsayed, Alberto Barrón-Cedeño, Paolo Papotti, Shaden Shaar, and Giovanni Da San Martino · 2021
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Multi-hop fact checking of political claims
Wojciech Ostrowski, Arnav Arora, Pepa Atanasova, and Isabelle Augenstein · 2021
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COVID-fact: Fact extraction and verification of real-world claims on COVID-19 pandemic
Arkadiy Saakyan, Tuhin Chakrabarty, and Smaranda Muresan · 2021
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Evidence-based fact-checking of health-related claims
Mourad Sarrouti, Asma Ben Abacha, Yassine Mrabet, and Dina Demner-Fushman · 2021
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Get your vitamin C! robust fact verification with contrastive evidence
Tal Schuster, Adam Fisch, and Regina Barzilay · 2021
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Generating literal and implied subquestions to fact-check complex claims
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Sebastião Miranda, Andreas Vlachos, David Nogueira, Andrew Secker, Afonso Mendes, Rebecca Garrett, Jeffrey J Mitchell, and Zita Marinho · 2019
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Document expansion by query prediction
Rodrigo Nogueira, Wei Yang, Jimmy Lin, and Kyunghyun Cho · 2019
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Climate-fever: A dataset for verification of real-world climate claims, 2020
Thomas Diggelmann, Jordan Boyd-Graber, Jannis Bulian, Massimiliano Ciaramita, and Markus Leippold · 2020
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Generating fact checking briefs
Angela Fan, Aleksandra Piktus, Fabio Petroni, Guillaume Wenzek, Marzieh Saeidi, Andreas Vlachos, Antoine Bordes, and Sebastian Riedel · 2020
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Explainable automated fact-checking: A survey
Neema Kotonya and Francesca Toni · 2020
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Debunking Handbook 2020
Stephan Lewandowsky, John Cook, Ullrich Ecker, Dolores Albarracin, Michelle Amazeen, Panayiota Kendeou, Doug Lombardi, Eryn Newman, Gordon Pennycook, Ethan Porter, David G. Rand, David N. Rapp, Jason Reifler, Jon Roozenbeek, Philipp Schmid, Colleen M. Seifert, Gale M. Sinatra, Briony Swire-Thompson, Sander van der Linden, Emily K. Vraga, Thomas J. Wood, and Maria S. Zaragoza · 2020
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BART: Denoising sequence-to-sequence pre-training for natural language generation, translation, and comprehension
Mike Lewis, Yinhan Liu, Naman Goyal, Marjan Ghazvininejad, Abdelrahman Mohamed, Omer Levy, Veselin Stoyanov, and Luke Zettlemoyer · 2020
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Jifan Chen, Aniruddh Sriram, Eunsol Choi, and Greg Durrett · 2022
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Missing counter-evidence renders nlp fact-checking unrealistic for misinformation, 2022
Max Glockner, Yufang Hou, and Iryna Gurevych · 2022
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CHEF: A pilot Chinese dataset for evidence-based fact-checking
Xuming Hu, Zhijiang Guo, GuanYu Wu, Aiwei Liu, Lijie Wen, and Philip Yu · 2022
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Investigating Reasons for Disagreement in Natural Language Inference
Nan-Jiang Jiang and Marie-Catherine de Marneffe · 2022
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Watclaimcheck: A new dataset for claim entailment and inference
Kashif Khan, Ruizhe Wang, and Pascal Poupart · 2022
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What makes good in-context examples for GPT-3?
Jiachang Liu, Dinghan Shen, Yizhe Zhang, Bill Dolan, Lawrence Carin, and Weizhu Chen · 2022
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Varifocal question generation for fact-checking
Nedjma Ousidhoum, Zhangdie Yuan, and Andreas Vlachos · 2022
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Learning to retrieve prompts for in-context learning
Ohad Rubin, Jonathan Herzig, and Jonathan Berant · 2022
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Bloom: A 176b-parameter open-access multilingual language model
Teven Le Scao, Angela Fan, Christopher Akiki, Ellie Pavlick, Suzana Ilić, Daniel Hesslow, Roman Castagné, Alexandra Sasha Luccioni, François Yvon, Matthias Gallé, et al · 2022
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Explainable fact-checking through question answering
Jing Yang, Didier Vega-Oliveros, Taís Seibt, and Anderson Rocha · 2022
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The challenges of online fact checking
Phoebe Arnold · 2023
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Vicuna: An open-source chatbot impressing gpt-4 with 90%* chatgpt quality, March 2023
Wei-Lin Chiang, Zhuohan Li, Zi Lin, Ying Sheng, Zhanghao Wu, Hao Zhang, Lianmin Zheng, Siyuan Zhuang, Yonghao Zhuang, Joseph E. Gonzalez, Ion Stoica, and Eric P. Xing · 2023
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How we’re using AI to scale up global fact checking
Andy Dudfield · 2023
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The intended uses of automated fact-checking artefacts: Why, how and who, 2023
Michael Schlichtkrull, Nedjma Ousidhoum, and Andreas Vlachos · 2023
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“liar, liar pants on fire”: A new benchmark dataset for fake news detection
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